Koichi Takayama
- Molecular Biology top 1%
- Oncology top 0.5%
- Pulmonary and Respiratory Medicine top 0.5%
- Immunology top 0.5%
- Epidemiology top 1%
- Co-authors
- N QureshiYoichi NakanishiE. RibiChikako KiyoharaNobuyuki HaraJ O KilburnPaolo MascagniJunji Uchino
- Topics
- Lung Cancer Treatments and Mutations (113 papers)Lung Cancer Research Studies (84 papers)Cancer Immunotherapy and Biomarkers (39 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryJournal of Clinical Oncology
- Partner nations
- JapanUnited StatesAustralia
In The Last Decade
Koichi Takayama
517 papers receiving 13.9k citations
Hit Papers
Peers
Comparison fields: 5 of 190
- Molecular Biology 4.8k
- Oncology 4.5k
- Pulmonary and Respiratory Medicine 3.0k
- Immunology 2.9k
- Epidemiology 1.6k
Countries citing papers authored by Koichi Takayama
This map shows the geographic impact of Koichi Takayama's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Koichi Takayama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Koichi Takayama more than expected).
Fields of papers citing papers by Koichi Takayama
This network shows the impact of papers produced by Koichi Takayama. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Koichi Takayama. The network helps show where Koichi Takayama may publish in the future.
Co-authorship network of co-authors of Koichi Takayama
This figure shows the co-authorship network connecting the top 25 collaborators of Koichi Takayama. A scholar is included among the top collaborators of Koichi Takayama based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Koichi Takayama. Koichi Takayama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 20 | |
| 3 | 5 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 7 | |
| 7 | 5 | |
| 8 | 4 | |
| 9 | 5 | |
| 10 | 3 | |
| 11 | 7 | |
| 12 | 33 | |
| 13 | 1 | |
| 14 | 20 | |
| 15 | 78 | |
| 16 | Induction of PD-L1 Expression by the EML4–ALK Oncoprotein and Downstream Signaling Pathways in Non–Small Cell Lung Cancerbreakdown → | 366 |
| 17 | 15 | |
| 18 | 188 | |
| 19 | 6 | |
| 20 | 68 |
About Koichi Takayama
Koichi Takayama is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Biotechnology, having authored 542 papers that have together received 14.4k indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (113 papers), Lung Cancer Research Studies (84 papers) and Cancer Immunotherapy and Biomarkers (39 papers). The work is most often cited by research in Oncology (4.5k citations), Immunology (2.9k citations) and Pulmonary and Respiratory Medicine (3.0k citations). Koichi Takayama has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include N Qureshi, Yoichi Nakanishi, E. Ribi, Chikako Kiyohara, Nobuyuki Hara, J O Kilburn, Paolo Mascagni, Junji Uchino, Taishi Harada and Tadaaki Yamada. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.